Progressive compressive imager

Sergei Evladov, Ofer Levi, Adrian Stern

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


We have designed and built a working automatic progressive sampling imaging system based on the vector sensor concept, which utilizes a unique sampling scheme of Radon projections. This sampling scheme makes it possible to progressively add information resulting in tradeoff between compression and the quality of reconstruction. The uniqueness of our sampling is that in any moment of the acquisition process the reconstruction can produce a reasonable version of the image. The advantage of the gradual addition of the samples is seen when the sparsity rate of the object is unknown, and thus the number of needed measurements. We have developed the iterative algorithm OSO (Ordered Sets Optimization) which employs our sampling scheme for creation of nearly uniform distributed sets of samples, which allows the reconstruction of Mega-Pixel images. We present the good quality reconstruction from compressed data ratios of 1:20.

Original languageEnglish
Title of host publicationCompressive Sensing
StatePublished - 23 Jul 2012
EventCompressive Sensing - Baltimore, MD, United States
Duration: 26 Apr 201227 Apr 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceCompressive Sensing
Country/TerritoryUnited States
CityBaltimore, MD


  • Ordered sets optimization
  • Progressive compressive imaging
  • Radon projections

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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